Significance estimation for large scale untargeted metabolomics annotations
Kerstin Scheubert, Franziska Hufsky, Daniel Petras, Mingxun Wang, Louis-Félix Nothias-Scaglia, Kai Dührkop, Nuno Bandeira, Pieter C. Dorrestein, Sebastian Böcker
The paper develops methods to estimate false discovery rates in untargeted metabolomics annotations and shows how adjusting spectral matching parameters can significantly increase the number of annotations.
Nature Communications · Nov 8, 2017Peer-reviewedBioinformatics